ggmcmc: Tools for Analyzing MCMC Simulations from Bayesian Inference
Version 1.1

Tools for assessing and diagnosing convergence of Markov Chain Monte Carlo simulations, as well as for graphically display results from full MCMC analysis. The package also facilitates the graphical interpretation of models by providing flexible functions to plot the results against observed variables.

Browse man pages Browse package API and functions Browse package files

AuthorXavier Fernández i Marín <xavier.fim@gmail.com>
Date of publication2016-06-28 23:48:06
MaintainerXavier Fernández i Marín <xavier.fim@gmail.com>
LicenseGPL-2
Version1.1
URL http://xavier-fim.net/packages/ggmcmc https://github.com/xfim/ggmcmc
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("ggmcmc")

Man pages

ac: Calculate the autocorrelation of a single chain, for a...
calc_bin: Calculate binwidths by parameter, based on the total number...
ci: Calculate Credible Intervals (wide and narrow).
custom.sort: Auxiliary function that sorts Parameter names taking into...
get_family: Subset a ggs object to get only the parameters with a given...
ggmcmc: Wrapper function that creates a single pdf file with all...
ggs: Import MCMC samples into a ggs object than can be used by all...
ggs_autocorrelation: Plot an autocorrelation matrix
ggs_caterpillar: Caterpillar plot with thick and thin CI
ggs_chain: Auxiliary function that extracts information from a single...
ggs_compare_partial: Density plots comparing the distribution of the whole chain...
ggs_crosscorrelation: Plot the Cross-correlation between-chains
ggs_density: Density plots of the chains
ggs_geweke: Dotplot of the Geweke diagnostic, the standard Z-score
ggs_histogram: Histograms of the paramters.
ggs_pairs: Create a plot matrix of posterior simulations
ggs_ppmean: Posterior predictive plot comparing the outcome mean vs the...
ggs_ppsd: Posterior predictive plot comparing the outcome standard...
ggs_Rhat: Dotplot of Potential Scale Reduction Factor (Rhat)
ggs_rocplot: Receiver-Operator Characteristic (ROC) plot for models with...
ggs_running: Running means of the chains
ggs_separation: Separation plot for models with binary response variables
ggs_traceplot: Traceplot of the chains
gl_unq: Generate a factor with unequal number of repetitions.
radon: Simulations of the parameters of a hierarchical model using...
roc_calc: Calculate the ROC curve for a set of observed outcomes and...
s: Simulations of the parameters of a simple linear regression...
s.binary: Simulations of the parameters of a simple linear regression...
sde0f: Spectral Density Estimate at Zero Frequency.
s.y.rep: Simulations of the posterior predictive distribution of a...
y: Values for the observed outcome of a simple linear regression...
y.binary: Values for the observed outcome of a binary logistic...

Functions

ac Man page Source code
calc_bin Man page Source code
ci Man page Source code
custom.sort Man page Source code
get_family Man page Source code
ggmcmc Man page Source code
ggmcmc-package Man page
ggs Man page Source code
ggs_Rhat Man page Source code
ggs_autocorrelation Man page Source code
ggs_caterpillar Man page Source code
ggs_chain Man page Source code
ggs_compare_partial Man page Source code
ggs_crosscorrelation Man page Source code
ggs_density Man page Source code
ggs_geweke Man page Source code
ggs_histogram Man page Source code
ggs_pairs Man page Source code
ggs_ppmean Man page Source code
ggs_ppsd Man page Source code
ggs_rocplot Man page Source code
ggs_running Man page Source code
ggs_separation Man page Source code
ggs_traceplot Man page Source code
gl_unq Man page Source code
radon Man page
roc_calc Man page Source code
s Man page
s.binary Man page
s.y.rep Man page
sde0f Man page Source code
y Man page
y.binary Man page

Files

inst
inst/CITATION
inst/doc
inst/doc/using_ggmcmc.html
inst/doc/v70i09.pdf
inst/doc/v70i09.R
inst/doc/using_ggmcmc.Rmd
inst/doc/using_ggmcmc.R
inst/doc/v70i09.Rnw
NAMESPACE
NEWS
data
data/linear.rda
data/radon.rda
data/binary.rda
R
R/ggs_histogram.R
R/ggs.R
R/ggs_crosscorrelation.R
R/ggs_separation.R
R/globals.R
R/data.R
R/ggs_Rhat.R
R/ggs_geweke.R
R/functions.R
R/help.R
R/ggs_autocorrelation.R
R/ggs_pairs.R
R/ggs_caterpillar.R
R/ggs_running.R
R/ggs_ppsd.R
R/ggmcmc.R
R/ggs_compare_partial.R
R/ggs_traceplot.R
R/ggs_ppmean.R
R/ggs_density.R
R/ggs_rocplot.R
vignettes
vignettes/bibliography.bib
vignettes/v70i09.bib
vignettes/using_ggmcmc.Rmd
vignettes/v70i09.Rnw
README.md
MD5
build
build/vignette.rds
DESCRIPTION
man
man/ci.Rd
man/ggs_autocorrelation.Rd
man/ggs_chain.Rd
man/gl_unq.Rd
man/ggs_traceplot.Rd
man/get_family.Rd
man/ggs_rocplot.Rd
man/ac.Rd
man/ggs_ppmean.Rd
man/ggs.Rd
man/ggs_compare_partial.Rd
man/sde0f.Rd
man/ggs_geweke.Rd
man/y.Rd
man/calc_bin.Rd
man/y.binary.Rd
man/ggs_Rhat.Rd
man/custom.sort.Rd
man/ggs_caterpillar.Rd
man/ggs_histogram.Rd
man/ggs_ppsd.Rd
man/s.binary.Rd
man/radon.Rd
man/s.y.rep.Rd
man/roc_calc.Rd
man/ggs_pairs.Rd
man/ggs_crosscorrelation.Rd
man/s.Rd
man/ggmcmc.Rd
man/ggs_separation.Rd
man/ggs_density.Rd
man/ggs_running.Rd
ggmcmc documentation built on May 20, 2017, 12:40 a.m.